The invention relates to methods for mutating and determining the physical stability and conformation of peptides. The method predicts the structure of a peptide and the effects of mutations on the structure and the physical stability of a peptide.
Peptide folding and structure prediction is complex due to the large number of atoms in a typical peptide. The large size of a peptide chain, in combination with its large number of degrees of freedom, allows it to adopt an immense number of conformations. For example, a relatively small polypeptide of 100 residues may exist in up to 10.sup.30 conformations. Despite the multitude of possible conformations, many peptides, even large proteins and enzymes fold in vivo into precise three-dimensional structures. The peptide generally folds back on itself creating numerous simultaneous interactions between different parts of the peptide. These interactions result in a stable three-dimensional structure that provides unique chemical environments and spatial orientations of functional groups that give the peptide its special structural and functional properties, as well as its physical stability. The ability to predict peptide structures and stabilities from knowledge of the constituent amino acids would be highly desirable.
Earlier efforts at peptide structure prediction have focused on prediction of side-chain conformation (given knowledge of the position of the main chain) as a less complex but nonetheless important portion of the "Protein Folding Problem." (For a description of the "Protein Folding Problem," see Richards, Scientific American (1991), vol 265, pg. 54, which is hereby incorporated by reference for all purposes.) Numerous methods attempt to predict protein conformation from a knowledge of the primary sequence. Examples of these methods are embodied in programs such as "Homology" by Biosym, "Biograf" by BioDesign, "Nemesis" by Oxford Molecular, "SYBYL" and "Composer" by Tripos Associates, "CHARMM" by Polygen, "AMBER" by UCSF, and "MM2" and "MMP2" by Molecular Design, Ltd. This list is meant to be illustrative rather than exhaustive.
Accurate prediction of amino acid side-chain conformation from the peptide primary sequence and a model of the peptide main chain would be highly useful.